code: def test_listwise_dense_layer(self):
      context_features, example_features = self._listwise_dense_layer(
          inputs=self._features, training=False
      )
      self.assertAllInSet(
          ["query_length"], set(six.iterkeys(context_features))
      )
      self.assertAllInSet(
          ["unigrams", "utility"], set(six.iterkeys(example_features))
      )
      self.assertAllEqual(
          example_features["unigrams"].get_shape().as_list(), [2, 2, 10]
      )
      self.assertAllEqual(context_features["query_length"], [[1], [2]])
      self.assertAllEqual(
          example_features["utility"],
          [
              [[tf.math.log1p(1.0)], [0.0]],
              [[0.0], [tf.math.log1p(1.0)]],
          ],
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import six
  import tensorflow.compat.v2
  from tensorflow_ranking.python.keras import feature
label_desc: Use image node_id 3 for calling the EncodeListwiseFeaturesTest obj's underlying member method code with example usage: obj.test_listwise_dense_layer() without return types